#install.packages("readr")
#library(readr)
library(ggplot2)
library(GGally)
## Registered S3 method overwritten by 'GGally':
##   method from   
##   +.gg   ggplot2
#install.packages("GGally")
url <- "https://github.gatech.edu/raw/MGT-6203-Fall-2023-Canvas/Team-18/main/Data/CarSpecs.csv?token=GHSAT0AAAAAAAAC26TN5RFNYUES5XH5SGNMZKFK6TQ"
cardataspec<-read.csv(url)
cardata <- cardataspec 
head(cardata)
##   Car.Year Car.Make Car.Model  MSRP X2019MSRP                   EPA.Class
## 1     2019    Acura      RDX  40600     40600 Small Sport Utility Vehicle
## 2     2019    Acura      RDX  45500     45500 Small Sport Utility Vehicle
## 3     2019    Acura      RDX  43600     43600 Small Sport Utility Vehicle
## 4     2019    Acura      RDX  37400     37400 Small Sport Utility Vehicle
## 5     2019    Acura      RDX  42600     42600 Small Sport Utility Vehicle
## 6     2019    Acura      RDX  47500     47500 Small Sport Utility Vehicle
##             Style.Name       Drive.Train Passenger.Capacity Passenger.Doors
## 1 FWD w/Technology Pkg Front Wheel Drive                  5               4
## 2    FWD w/Advance Pkg Front Wheel Drive                  5               4
## 3     FWD w/A-Spec Pkg Front Wheel Drive                  5               4
## 4                  FWD Front Wheel Drive                  5               4
## 5 AWD w/Technology Pkg   All Wheel Drive                  5               4
## 6    AWD w/Advance Pkg   All Wheel Drive                  5               4
##      Body.Style Transmittion.Speed Base.Curb.Weight Wheelbase Height.Overall
## 1 Sport Utility                 10             3790     108.3           65.7
## 2 Sport Utility                 10             3829     108.3           65.7
## 3 Sport Utility                 10             3821     108.3           65.7
## 4 Sport Utility                 10             3783     108.3           65.7
## 5 Sport Utility                 10             4026     108.3           65.7
## 6 Sport Utility                 10             4068     108.3           65.7
##   Fuel.Tank.Capacity Combined.Estimate.MPG City.MPG Hwy.MPG SAE.Net.Torque
## 1               17.1                    24       22      28            280
## 2               17.1                    24       22      28            280
## 3               17.1                    24       22      27            280
## 4               17.1                    24       22      28            280
## 5               17.1                    23       21      27            280
## 6               17.1                    23       21      27            280
##          Fuel.System Engine.Type SAE.Net.Horsepower Transmittion.Description
## 1 Gasoline Injection          I4                272                Automatic
## 2 Gasoline Injection          I4                272                Automatic
## 3 Gasoline Injection          I4                272                Automatic
## 4 Gasoline Injection          I4                272                Automatic
## 5 Gasoline Injection          I4                272                Automatic
## 6 Gasoline Injection          I4                272                Automatic
##     Brake.Type     Steering.Type Front.Tire.Size Rear.Tire.Size
## 1 4-Wheel Disc Power Rack-Pinion     P235/55HR19    P235/55HR19
## 2 4-Wheel Disc Power Rack-Pinion     P235/55HR19    P235/55HR19
## 3 4-Wheel Disc Power Rack-Pinion     P255/45VR20    P255/45VR20
## 4 4-Wheel Disc Power Rack-Pinion     P235/55HR19    P235/55HR19
## 5 4-Wheel Disc Power Rack-Pinion     P235/55HR19    P235/55HR19
## 6 4-Wheel Disc Power Rack-Pinion     P235/55HR19    P235/55HR19
##   Front.Tire.Material Back.Tire.Material Suspension.Type.Front
## 1            Aluminum           Aluminum                 Strut
## 2            Aluminum           Aluminum                 Strut
## 3            Aluminum           Aluminum                 Strut
## 4            Aluminum           Aluminum                 Strut
## 5            Aluminum           Aluminum                 Strut
## 6            Aluminum           Aluminum                 Strut
##   Suspension.Type.Rear Brakes.ABS Child.Safety.Rear.Door.Locks
## 1           Multi-Link        Yes                          Yes
## 2           Multi-Link        Yes                          Yes
## 3           Multi-Link        Yes                          Yes
## 4           Multi-Link        Yes                          Yes
## 5           Multi-Link        Yes                          Yes
## 6           Multi-Link        Yes                          Yes
##   Daytime.Running.Lights Traction.Control Night.Vision Rollover.Protection.Bars
## 1                    Yes              Yes           No                       No
## 2                    Yes              Yes           No                       No
## 3                    Yes              Yes           No                       No
## 4                    Yes              Yes           No                       No
## 5                    Yes              Yes           No                       No
## 6                    Yes              Yes           No                       No
##   Fog.Lamps Parking.Aid Tire.Pressure.Monitor BackUp.Camera Stability.Control
## 1        No         Yes                   Yes           Yes               Yes
## 2       Yes         Yes                   Yes           Yes               Yes
## 3       Yes         Yes                   Yes           Yes               Yes
## 4        No          No                   Yes           Yes               Yes
## 5        No         Yes                   Yes           Yes               Yes
## 6       Yes         Yes                   Yes           Yes               Yes
dim(cardata)
## [1] 4861   43
str(cardata)
## 'data.frame':    4861 obs. of  43 variables:
##  $ Car.Year                    : int  2019 2019 2019 2019 2019 2019 2019 2018 2018 2018 ...
##  $ Car.Make                    : chr  "Acura" "Acura" "Acura" "Acura" ...
##  $ Car.Model                   : chr  "RDX " "RDX " "RDX " "RDX " ...
##  $ MSRP                        : int  40600 45500 43600 37400 42600 47500 45600 37500 41000 39700 ...
##  $ X2019MSRP                   : int  40600 45500 43600 37400 42600 47500 45600 38179 41742 40419 ...
##  $ EPA.Class                   : chr  "Small Sport Utility Vehicle" "Small Sport Utility Vehicle" "Small Sport Utility Vehicle" "Small Sport Utility Vehicle" ...
##  $ Style.Name                  : chr  "FWD w/Technology Pkg" "FWD w/Advance Pkg" "FWD w/A-Spec Pkg" "FWD" ...
##  $ Drive.Train                 : chr  "Front Wheel Drive" "Front Wheel Drive" "Front Wheel Drive" "Front Wheel Drive" ...
##  $ Passenger.Capacity          : int  5 5 5 5 5 5 5 5 5 5 ...
##  $ Passenger.Doors             : int  4 4 4 4 4 4 4 4 4 4 ...
##  $ Body.Style                  : chr  "Sport Utility" "Sport Utility" "Sport Utility" "Sport Utility" ...
##  $ Transmittion.Speed          : int  10 10 10 10 10 10 10 6 6 6 ...
##  $ Base.Curb.Weight            : int  3790 3829 3821 3783 4026 4068 4015 3902 3772 3768 ...
##  $ Wheelbase                   : num  108 108 108 108 108 ...
##  $ Height.Overall              : num  65.7 65.7 65.7 65.7 65.7 65.7 65.7 65 65 65 ...
##  $ Fuel.Tank.Capacity          : num  17.1 17.1 17.1 17.1 17.1 17.1 17.1 16 16 16 ...
##  $ Combined.Estimate.MPG       : int  24 24 24 24 23 23 23 22 23 23 ...
##  $ City.MPG                    : int  22 22 22 22 21 21 21 19 20 20 ...
##  $ Hwy.MPG                     : int  28 28 27 28 27 27 26 27 28 28 ...
##  $ SAE.Net.Torque              : int  280 280 280 280 280 280 280 252 252 252 ...
##  $ Fuel.System                 : chr  "Gasoline Injection" "Gasoline Injection" "Gasoline Injection" "Gasoline Injection" ...
##  $ Engine.Type                 : chr  "I4" "I4" "I4" "I4" ...
##  $ SAE.Net.Horsepower          : int  272 272 272 272 272 272 272 279 279 279 ...
##  $ Transmittion.Description    : chr  "Automatic" "Automatic" "Automatic" "Automatic" ...
##  $ Brake.Type                  : chr  "4-Wheel Disc" "4-Wheel Disc" "4-Wheel Disc" "4-Wheel Disc" ...
##  $ Steering.Type               : chr  "Power Rack-Pinion" "Power Rack-Pinion" "Power Rack-Pinion" "Power Rack-Pinion" ...
##  $ Front.Tire.Size             : chr  "P235/55HR19" "P235/55HR19" "P255/45VR20" "P235/55HR19" ...
##  $ Rear.Tire.Size              : chr  "P235/55HR19" "P235/55HR19" "P255/45VR20" "P235/55HR19" ...
##  $ Front.Tire.Material         : chr  "Aluminum" "Aluminum" "Aluminum" "Aluminum" ...
##  $ Back.Tire.Material          : chr  "Aluminum" "Aluminum" "Aluminum" "Aluminum" ...
##  $ Suspension.Type.Front       : chr  "Strut" "Strut" "Strut" "Strut" ...
##  $ Suspension.Type.Rear        : chr  "Multi-Link" "Multi-Link" "Multi-Link" "Multi-Link" ...
##  $ Brakes.ABS                  : chr  "Yes" "Yes" "Yes" "Yes" ...
##  $ Child.Safety.Rear.Door.Locks: chr  "Yes" "Yes" "Yes" "Yes" ...
##  $ Daytime.Running.Lights      : chr  "Yes" "Yes" "Yes" "Yes" ...
##  $ Traction.Control            : chr  "Yes" "Yes" "Yes" "Yes" ...
##  $ Night.Vision                : chr  "No" "No" "No" "No" ...
##  $ Rollover.Protection.Bars    : chr  "No" "No" "No" "No" ...
##  $ Fog.Lamps                   : chr  "No" "Yes" "Yes" "No" ...
##  $ Parking.Aid                 : chr  "Yes" "Yes" "Yes" "No" ...
##  $ Tire.Pressure.Monitor       : chr  "Yes" "Yes" "Yes" "Yes" ...
##  $ BackUp.Camera               : chr  "Yes" "Yes" "Yes" "Yes" ...
##  $ Stability.Control           : chr  "Yes" "Yes" "Yes" "Yes" ...
# Finding the Column names/Variable names
names(cardata)
##  [1] "Car.Year"                     "Car.Make"                    
##  [3] "Car.Model"                    "MSRP"                        
##  [5] "X2019MSRP"                    "EPA.Class"                   
##  [7] "Style.Name"                   "Drive.Train"                 
##  [9] "Passenger.Capacity"           "Passenger.Doors"             
## [11] "Body.Style"                   "Transmittion.Speed"          
## [13] "Base.Curb.Weight"             "Wheelbase"                   
## [15] "Height.Overall"               "Fuel.Tank.Capacity"          
## [17] "Combined.Estimate.MPG"        "City.MPG"                    
## [19] "Hwy.MPG"                      "SAE.Net.Torque"              
## [21] "Fuel.System"                  "Engine.Type"                 
## [23] "SAE.Net.Horsepower"           "Transmittion.Description"    
## [25] "Brake.Type"                   "Steering.Type"               
## [27] "Front.Tire.Size"              "Rear.Tire.Size"              
## [29] "Front.Tire.Material"          "Back.Tire.Material"          
## [31] "Suspension.Type.Front"        "Suspension.Type.Rear"        
## [33] "Brakes.ABS"                   "Child.Safety.Rear.Door.Locks"
## [35] "Daytime.Running.Lights"       "Traction.Control"            
## [37] "Night.Vision"                 "Rollover.Protection.Bars"    
## [39] "Fog.Lamps"                    "Parking.Aid"                 
## [41] "Tire.Pressure.Monitor"        "BackUp.Camera"               
## [43] "Stability.Control"
# Finding Numerical Variable
numeric_cardata_col <- colnames(cardata[,sapply(cardata,is.numeric)])
numeric_cardata_col
##  [1] "Car.Year"              "MSRP"                  "X2019MSRP"            
##  [4] "Passenger.Capacity"    "Passenger.Doors"       "Transmittion.Speed"   
##  [7] "Base.Curb.Weight"      "Wheelbase"             "Height.Overall"       
## [10] "Fuel.Tank.Capacity"    "Combined.Estimate.MPG" "City.MPG"             
## [13] "Hwy.MPG"               "SAE.Net.Torque"        "SAE.Net.Horsepower"
cardata_num <- cardata[,c('MSRP','Car.Year','X2019MSRP','Passenger.Capacity','Passenger.Doors','Transmittion.Speed','Base.Curb.Weight','Wheelbase','Height.Overall','Fuel.Tank.Capacity','Combined.Estimate.MPG','City.MPG','Hwy.MPG','SAE.Net.Torque','SAE.Net.Horsepower')]
# Correlation Matrix of Numerical Variable
library(corrplot)
## corrplot 0.92 loaded
c1_6 = round(cor(cardata_num[1:6]),2)
corrplot(c1_6,method ="number")

c7_11 = round(cor(cardata_num[,c(1,7:11)]),2)
corrplot(c7_11,method ="number")

c12_15 = round(cor(cardata_num[,c(1,12:15)]),2)
corrplot(c12_15,method ="number")

ggcorr(cardata_num)

unique(cardata$Car.Year)
## [1] 2019 2018 2016 2015
unique(cardata$Car.Make)
##  [1] "Acura"         "Alfa"          "Aston"         "Audi"         
##  [5] "Bentley"       "BMW"           "Buick"         "Cadillac"     
##  [9] "Chevrolet"     "Chrysler"      "Dodge"         "Ferrari"      
## [13] "FIAT"          "Ford"          "Genesis"       "GMC"          
## [17] "Honda"         "Hyundai"       "INFINITI"      "Jaguar"       
## [21] "Jeep"          "Kia"           "Lamborghini"   "Land"         
## [25] "Lexus"         "Lincoln"       "Lotus"         "Maserati"     
## [29] "Mazda"         "McLaren"       "Mercedes-Benz" "MINI"         
## [33] "Mitsubishi"    "Nissan"        "Porsche"       "Ram"          
## [37] "Rolls-Royce"   "smart"         "Subaru"        "Toyota"       
## [41] "Volkswagen"    "Volvo"
#unique(cardata$Car.Model)
#unique(cardata$EPA.Class)
#unique(cardata$Style.Name)
#unique(cardata$Drive.Train)
#unique(cardata$Body.Style)
# Car.Make Vs MSRP & Car.Model Vs MSRP

library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.2     ✔ readr     2.1.4
## ✔ forcats   1.0.0     ✔ stringr   1.5.0
## ✔ lubridate 1.9.3     ✔ tibble    3.2.1
## ✔ purrr     1.0.2     ✔ tidyr     1.3.0
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
cardata %>%
  ggplot() +
    aes(y = MSRP, x = Car.Make, group = "") +
    geom_point() + 
    geom_line()+theme(axis.text.x  = element_text(angle=90, vjust=0.5, size=8))

cardata %>%
  ggplot() +
    aes(y = Car.Model, x = Car.Make, group = "") +
    geom_point() + 
    geom_line()+theme(axis.text.x  = element_text(angle=90, vjust=0.5, size=8))

unique(cardata$Car.Model)
##   [1] "RDX "                        "MDX "                       
##   [3] "TLX "                        "ILX "                       
##   [5] "NSX "                        "RLX "                       
##   [7] "Romeo 4C "                   "Romeo Giulia "              
##   [9] "Romeo Stelvio Quadrifoglio " "Romeo Stelvio "             
##  [11] "Romeo 4C Spider "            "Martin DB11 "               
##  [13] "Martin Vanquish "            "A6 "                        
##  [15] "A7 "                         "Q3 "                        
##  [17] "S3 "                         "Q5 "                        
##  [19] "S7 "                         "S4 "                        
##  [21] "Q7 "                         "A4 "                        
##  [23] "S6 "                         "A5 "                        
##  [25] "A5 Sportback "               "SQ5 "                       
##  [27] "RS 3 "                       "S5 Coupe "                  
##  [29] "S5 Sportback "               "A4 allroad "                
##  [31] "S5 Cabriolet "               "RS 7 "                      
##  [33] "TT "                         "A8 L "                      
##  [35] "S8 plus "                    "TT Coupe "                  
##  [37] "RS 5 Coupe "                 "TTS "                       
##  [39] "RS 5 Sportback "             "TT Roadster "               
##  [41] "Continental GT "             "Flying Spur "               
##  [43] "Mulsanne "                   "3-Series "                  
##  [45] "X5 "                         "X3 "                        
##  [47] "8-Series "                   "M3 "                        
##  [49] "5-Series "                   "X1 "                        
##  [51] "4-Series "                   "X4 "                        
##  [53] "Z4 "                         "M4 "                        
##  [55] "M2 "                         "X6 "                        
##  [57] "7-Series "                   "6-Series "                  
##  [59] "2-Series "                   "M5 "                        
##  [61] "M6 "                         "Encore "                    
##  [63] "Enclave "                    "Lacrosse "                  
##  [65] "Regal "                      "Cascada "                   
##  [67] "Envision "                   "Regal TourX "               
##  [69] "Regal Sportback "            "XT4 "                       
##  [71] "XT5 "                        "CT6 "                       
##  [73] "XTS "                        "CTS "                       
##  [75] "CTS-V "                      "ATS Coupe "                 
##  [77] "ATS Sedan "                  "ATS-V Coupe "               
##  [79] "ATS-V Sedan "                "Blazer "                    
##  [81] "Corvette "                   "Camaro "                    
##  [83] "Equinox "                    "Traverse "                  
##  [85] "Malibu "                     "Cruze "                     
##  [87] "Spark "                      "Impala "                    
##  [89] "Trax "                       "Sonic "                     
##  [91] "Pacifica "                   "300"                        
##  [93] "Challenger "                 "Charger "                   
##  [95] "Journey "                    "Grand Caravan "             
##  [97] "488 GTB "                    "488 Spider "                
##  [99] "California T "               "812 Superfast "             
## [101] "GTC4Lusso "                  "500X "                      
## [103] "124 Spider "                 "500"                        
## [105] "500L "                       "Mustang "                   
## [107] "Explorer "                   "Escape "                    
## [109] "Edge "                       "Focus "                     
## [111] "Ecosport "                   "Fusion "                    
## [113] "Transit Connect Wagon "      "Taurus "                    
## [115] "Fiesta "                     "Flex "                      
## [117] "G70 "                        "G80 "                       
## [119] "G90 "                        "Acadia "                    
## [121] "Terrain "                    "Civic "                     
## [123] "Civic Coupe "                "Pilot "                     
## [125] "Odyssey "                    "Passport "                  
## [127] "HR-V "                       "Fit "                       
## [129] "Accord Sedan "               "Civic Hatchback "           
## [131] "Civic Si Sedan "             "Civic Type R "              
## [133] "Civic Si Coupe "             "Santa Fe "                  
## [135] "Tucson "                     "Veloster "                  
## [137] "Elantra "                    "Santa Fe Sport "            
## [139] "Sonata "                     "Kona "                      
## [141] "Accent "                     "Santa Fe XL "               
## [143] "IONIQ Hybrid "               "Sonata Hybrid "             
## [145] "QX50 "                       "Q50 "                       
## [147] "Q70 "                        "Q60 "                       
## [149] "QX30 "                       "F-Pace "                    
## [151] "F-Type "                     "XE "                        
## [153] "XF "                         "XJ "                        
## [155] "E-Pace "                     "Cherokee "                  
## [157] "Grand Cherokee "             "Compass "                   
## [159] "Renegade "                   "Sorento "                   
## [161] "Sportage "                   "Optima "                    
## [163] "Niro "                       "Forte "                     
## [165] "Soul "                       "Optima Hybrid "             
## [167] "Rio "                        "K900 "                      
## [169] "Sedona "                     "Cadenza "                   
## [171] "Rio 5-door "                 "Aventador "                 
## [173] "Huracan "                    "Rover Range Rover Sport "   
## [175] "Rover Range Rover Evoque "   "UX "                        
## [177] "ES "                         "RX "                        
## [179] "RC F "                       "GS F "                      
## [181] "NX "                         "IS "                        
## [183] "GS "                         "RC "                        
## [185] "LS "                         "LC "                        
## [187] "Nautilus "                   "MKC "                       
## [189] "Continental "                "MKX "                       
## [191] "MKZ "                        "MKT "                       
## [193] "Evora "                      "Ghibli "                    
## [195] "Levante "                    "GranTurismo "               
## [197] "Quattroporte "               "MAZDA3 "                    
## [199] "MAZDA6 "                     "MX-5 Miata "                
## [201] "CX-3 "                       "CX-5 "                      
## [203] "CX-9 "                       "MX-5 Miata RF "             
## [205] "Mazda3 5-Door "              "Mazda3 4-Door "             
## [207] "570GT "                      "720S "                      
## [209] "570S "                       "A Class "                   
## [211] "C Class "                    "CLA Class "                 
## [213] "GLE Class "                  "GLC Class "                 
## [215] "CLS Class "                  "GLA Class "                 
## [217] "SL Class "                   "E Class "                   
## [219] "SLC Class "                  "S Class "                   
## [221] "AMG GT "                     "Cooper "                    
## [223] "Cooper Countryman "          "Hardtop 2 Door "            
## [225] "Clubman "                    "Hardtop 4 Door "            
## [227] "Convertible "                "Mirage "                    
## [229] "Outlander "                  "Eclipse Cross "             
## [231] "Outlander Sport "            "Mirage G4 "                 
## [233] "370Z "                       "Versa "                     
## [235] "Sentra "                     "GT-R "                      
## [237] "370Z Coupe "                 "370Z Roadster "             
## [239] "Macan "                      "Panamera "                  
## [241] "911"                         "718"                        
## [243] "718 Cayman "                 "ProMaster City "            
## [245] "Phantom "                    "Ghost "                     
## [247] "Wraith "                     "Dawn "                      
## [249] "fortwo "                     "Forester "                  
## [251] "Crosstrek "                  "Outback "                   
## [253] "WRX "                        "Legacy "                    
## [255] "Impreza "                    "BRZ "                       
## [257] "RAV4 "                       "Corolla "                   
## [259] "Avalon "                     "Highlander "                
## [261] "Yaris "                      "Camry "                     
## [263] "Sienna "                     "86"                         
## [265] "Corolla Hatchback "          "Yaris iA "                  
## [267] "Yaris Sedan "                "Corolla iM "                
## [269] "Jetta "                      "Tiguan "                    
## [271] "Passat "                     "Golf "                      
## [273] "Beetle "                     "Tiguan Limited "            
## [275] "Golf Alltrack "              "Golf R "                    
## [277] "Beetle Convertible "         "XC40 "                      
## [279] "XC60 "                       "V60 "                       
## [281] "V90 "                        "S60 "                       
## [283] "XC90 "                       "S90 "                       
## [285] "V60 Cross Country "
# From the graph, it shows that Car.Make == "Lamborghini" has the highest MRSP
highest_MRSP <- cardata[which.max(cardata$MSRP),]
highest_MRSP
##      Car.Year    Car.Make  Car.Model   MSRP X2019MSRP   EPA.Class
## 2992     2015 Lamborghini Aventador  548800    591936 Two Seaters
##                      Style.Name     Drive.Train Passenger.Capacity
## 2992 2dr Conv 50th Anniversario All Wheel Drive                  2
##      Passenger.Doors  Body.Style Transmittion.Speed Base.Curb.Weight Wheelbase
## 2992               2 Convertible                  7             4196     106.3
##      Height.Overall Fuel.Tank.Capacity Combined.Estimate.MPG City.MPG Hwy.MPG
## 2992           44.7               23.8                    12       10      16
##      SAE.Net.Torque        Fuel.System Engine.Type SAE.Net.Horsepower
## 2992            508 Gasoline Injection         V12                720
##      Transmittion.Description   Brake.Type     Steering.Type Front.Tire.Size
## 2992                   Manual 4-Wheel Disc Power Rack-Pinion     P255/35YR19
##      Rear.Tire.Size Front.Tire.Material Back.Tire.Material
## 2992    P335/30YR20            Aluminum           Aluminum
##        Suspension.Type.Front    Suspension.Type.Rear Brakes.ABS
## 2992 Double Wishbone Pushrod Double Wishbone Pushrod        Yes
##      Child.Safety.Rear.Door.Locks Daytime.Running.Lights Traction.Control
## 2992                           No                    Yes              Yes
##      Night.Vision Rollover.Protection.Bars Fog.Lamps Parking.Aid
## 2992           No                      Yes        No          No
##      Tire.Pressure.Monitor BackUp.Camera Stability.Control
## 2992                   Yes            No               Yes
highest_MRSP_car <- cardata[cardata$Car.Make == "Lamborghini",]
highest_MRSP_car %>%
  ggplot() +
    aes(y = MSRP, x = Car.Model, group = "") +
    geom_point() + 
    geom_line()+theme(axis.text.x  = element_text(angle=90, vjust=0.5, size=8))

Lowest_MRSP <- cardata[which.min(cardata$MSRP),]
Lowest_MRSP
##      Car.Year Car.Make Car.Model  MSRP X2019MSRP    EPA.Class
## 3816     2016   Nissan    Versa  11990     12772 Compact Cars
##                Style.Name       Drive.Train Passenger.Capacity Passenger.Doors
## 3816 4dr Sdn Manual 1.6 S Front Wheel Drive                  5               4
##      Body.Style Transmittion.Speed Base.Curb.Weight Wheelbase Height.Overall
## 3816    4dr Car                  5             2363     102.4           59.6
##      Fuel.Tank.Capacity Combined.Estimate.MPG City.MPG Hwy.MPG SAE.Net.Torque
## 3816               10.8                    30       27      36            107
##             Fuel.System Engine.Type SAE.Net.Horsepower Transmittion.Description
## 3816 Gasoline Injection          I4                109                   Manual
##                Brake.Type     Steering.Type Front.Tire.Size Rear.Tire.Size
## 3816 Front Disc/Rear Drum Power Rack-Pinion     P185/65HR15    P185/65HR15
##      Front.Tire.Material Back.Tire.Material Suspension.Type.Front
## 3816               Steel              Steel                 Strut
##      Suspension.Type.Rear Brakes.ABS Child.Safety.Rear.Door.Locks
## 3816         Torsion Beam        Yes                          Yes
##      Daytime.Running.Lights Traction.Control Night.Vision
## 3816                     No              Yes           No
##      Rollover.Protection.Bars Fog.Lamps Parking.Aid Tire.Pressure.Monitor
## 3816                       No        No          No                   Yes
##      BackUp.Camera Stability.Control
## 3816            No               Yes
# From the above R code, it shows that Car.Make == "Nissan" has the lowest MRSP
Lowest_MRSP_car <- cardata[cardata$Car.Make == "Nissan",]
Lowest_MRSP_car %>%
  ggplot() +
    aes(y = MSRP, x = Car.Model, group = "") +
    geom_point() + 
    geom_line()+theme(axis.text.x  = element_text(angle=90, vjust=0.5, size=8))

# Finding the median of MRSP
med <- median(cardata$MSRP)
Median_car <- cardata[cardata$MSRP == 37710,]
Median_car
##      Car.Year Car.Make Car.Model  MSRP X2019MSRP EPA.Class Style.Name
## 1920     2019    Honda  Odyssey  37710     37710   Minivan  EX-L Auto
##            Drive.Train Passenger.Capacity Passenger.Doors          Body.Style
## 1920 Front Wheel Drive                  8               4 Mini-van, Passenger
##      Transmittion.Speed Base.Curb.Weight Wheelbase Height.Overall
## 1920                  9             4471     118.1           69.6
##      Fuel.Tank.Capacity Combined.Estimate.MPG City.MPG Hwy.MPG SAE.Net.Torque
## 1920               19.5                    22       19      28            262
##             Fuel.System Engine.Type SAE.Net.Horsepower Transmittion.Description
## 1920 Gasoline Injection          V6                280                Automatic
##        Brake.Type     Steering.Type Front.Tire.Size Rear.Tire.Size
## 1920 4-Wheel Disc Power Rack-Pinion     P235/60HR18    P235/60HR18
##      Front.Tire.Material Back.Tire.Material Suspension.Type.Front
## 1920            Aluminum           Aluminum                 Strut
##      Suspension.Type.Rear Brakes.ABS Child.Safety.Rear.Door.Locks
## 1920         Trailing Arm        Yes                          Yes
##      Daytime.Running.Lights Traction.Control Night.Vision
## 1920                    Yes              Yes           No
##      Rollover.Protection.Bars Fog.Lamps Parking.Aid Tire.Pressure.Monitor
## 1920                       No       Yes          No                   Yes
##      BackUp.Camera Stability.Control
## 1920           Yes               Yes
Median_car1 <- cardata[cardata$Car.Make == "Honda",]

Median_car1 %>%
  ggplot() +
    aes(y = MSRP, x = Car.Model, group = "") +
    geom_point() + 
    geom_line()+theme(axis.text.x  = element_text(angle=90, vjust=0.5, size=8))

plot(cardata_num)

par(mfrow=c(2,3))
plot(cardata_num$Car.Year, cardata_num$MSRP, main="Car.Year Vs MSRP", xlab="Car.Year", ylab="MSRP", col="red", cex=2)
plot(cardata_num$X2019MSRP, cardata_num$MSRP, main="X2019MSRP Vs MSRP", xlab="X2019MSRP", ylab="MSRP", col="red", cex=2)
plot(cardata_num$Passenger.Capacity, cardata_num$MSRP, main="Passenger.Capacity Vs MSRP", xlab="Passenger.Capacity", ylab="MSRP", col="red", cex=2)
plot(cardata_num$Passenger.Doors, cardata_num$MSRP, main="Passenger.Doors Vs MSRP", xlab="Passenger.Doors", ylab="MSRP", col="red", cex=2)
plot(cardata_num$Transmittion.Speed, cardata_num$MSRP, main="Transmittion.Speed Vs MSRP", xlab="Transmittion.Speed", ylab="MSRP", col="red", cex=2)
plot(cardata_num$Base.Curb.Weight, cardata_num$MSRP, main="Base.Curb.Weight Vs MSRP", xlab="Base.Curb.Weight", ylab="MSRP", col="red", cex=2)

par(mfrow=c(3,3))
plot(cardata_num$Wheelbase, cardata_num$MSRP, main="Wheelbase Vs MSRP", xlab="Wheelbase", ylab="MSRP", col="red", cex=2)
plot(cardata_num$Height.Overall, cardata_num$MSRP, main="Height.Overall Vs MSRP", xlab="Height.Overall", ylab="MSRP", col="red", cex=2)
plot(cardata_num$Fuel.Tank.Capacity, cardata_num$MSRP, main="Fuel.Tank.Capacity Vs MSRP", xlab="Fuel.Tank.Capacity", ylab="MSRP", col="red", cex=2)
plot(cardata_num$Combined.Estimate.MPG, cardata_num$MSRP, main="Combined.Estimate.MPG Vs MSRP", xlab="Combined.Estimate.MPG", ylab="MSRP", col="red", cex=2)
plot(cardata_num$City.MPG, cardata_num$MSRP, main="City.MPG Vs MSRP", xlab="City.MPG", ylab="MSRP", col="red", cex=2)
plot(cardata_num$Hwy.MPG, cardata_num$MSRP, main="Hwy.MPG Vs MSRP", xlab="Hwy.MPG", ylab="MSRP", col="red", cex=2)
plot(cardata_num$SAE.Net.Torque, cardata_num$MSRP, main="SAE.Net.Torque Vs MSRP", xlab="SAE.Net.Torque", ylab="MSRP", col="red", cex=2)
plot(cardata_num$SAE.Net.Horsepower, cardata_num$MSRP, main="SAE.Net.Horsepower Vs MSRP", xlab="SAE.Net.Horsepower", ylab="MSRP", col="red", cex=2)

boxplot(cardata$MSRP~as.factor(cardata$EPA.Class),main="EPA.Class Vs MSRP",xlab="EPA.Class",ylab="MSRP",col="yellow",border="red")

boxplot(cardata$MSRP~as.factor(cardata$Drive.Train),main="Drive.Train Vs MSRP",xlab="Drive.Train",ylab="MSRP",col="yellow",border="red")

boxplot(cardata$MSRP~as.factor(cardata$Body.Style),main="Body.Style Vs MSRP",xlab="Body.Style",ylab="MSRP",col="yellow",border="red")

boxplot(cardata$MSRP~as.factor(cardata$Fuel.System),main="Fuel.System Vs MSRP",xlab="Fuel.System",ylab="MSRP",col="yellow",border="red")

boxplot(cardata$MSRP~as.factor(cardata$Engine.Type),main="Engine.Type Vs MSRP",xlab="Engine.Type",ylab="MSRP",col="orange",border="brown")

boxplot(cardata$MSRP~as.factor(cardata$Transmittion.Description),main="Transmittion.Description Vs MSRP",xlab="Transmittion.Description",ylab="MSRP",col="orange",border="brown")

boxplot(cardata$MSRP~as.factor(cardata$Brake.Type),main="Brake.Type Vs MSRP",xlab="Brake.Type",ylab="MSRP",col="orange",border="brown")

boxplot(cardata$MSRP~as.factor(cardata$Steering.Type),main="Steering.Type Vs MSRP",xlab="Steering.Type",ylab="MSRP",col="orange",border="brown")

boxplot(cardata$MSRP~as.factor(cardata$Front.Tire.Material),main="Front.Tire.Material Vs MSRP",xlab="Front.Tire.Material",ylab="MSRP",col="yellow",border="blue")

boxplot(cardata$MSRP~as.factor(cardata$Back.Tire.Material),main="Back.Tire.Material Vs MSRP",xlab="Back.Tire.Material",ylab="MSRP",col="yellow",border="black")

boxplot(cardata$MSRP~as.factor(cardata$Suspension.Type.Front),main="Suspension.Type.Front Vs MSRP",xlab="Suspension.Type.Front",ylab="MSRP",col="yellow",border="blue")

boxplot(cardata$MSRP~as.factor(cardata$Suspension.Type.Rear),main="Suspension.Type.Rear Vs MSRP",xlab="Suspension.Type.Rear",ylab="MSRP",col="yellow",border="black")

boxplot(cardata$MSRP~as.factor(cardata$Brakes.ABS),main="Brakes.ABS Vs MSRP",xlab="Brakes.ABS",ylab="MSRP",col="orange",border="brown")

boxplot(cardata$MSRP~cardata$Child.Safety.Rear.Door.Locks,main="Child.Safety.Rear.Door.Locks Vs MSRP",xlab="Child.Safety.Rear.Door.Locks",ylab="MSRP",col="orange",border="brown")

boxplot(cardata$MSRP~as.factor(cardata$Daytime.Running.Lights),main="Daytime.Running.Lights Vs MSRP",xlab="Daytime.Running.Lights",ylab="MSRP",col="orange",border="brown")

boxplot(cardata$MSRP~as.factor(cardata$Traction.Control),main="Traction.Control Vs MSRP",xlab="Traction.Control",ylab="MSRP",col="orange",border="brown")

boxplot(cardata$MSRP~as.factor(cardata$Night.Vision),main="Night.Vision Vs MSRP",xlab="Night.Vision",ylab="MSRP",col="orange",border="brown")

boxplot(cardata$MSRP~as.factor(cardata$Rollover.Protection.Bars),main="Rollover.Protection.Bars Vs MSRP",xlab="Rollover.Protection.Bars",ylab="MSRP",col="orange",border="brown")

boxplot(cardata$MSRP~as.factor(cardata$Fog.Lamps),main="Fog.Lamps Vs MSRP",xlab="Fog.Lamps",ylab="MSRP",col="gold",border="black")

boxplot(cardata$MSRP~as.factor(cardata$Parking.Aid),main="Parking.Aid Vs MSRP",xlab="Parking.Aid",ylab="MSRP",col="gold",border="black")

boxplot(cardata$MSRP~as.factor(cardata$Tire.Pressure.Monitor),main="Tire.Pressure.Monitor Vs MSRP",xlab="Tire.Pressure.Monitor",ylab="MSRP",col="gold",border="black")

boxplot(cardata$MSRP~as.factor(cardata$BackUp.Camera),main="BackUp.Camera Vs MSRP",xlab="BackUp.Camera",ylab="MSRP",col="gold",border="black")

boxplot(cardata$MSRP~as.factor(cardata$Stability.Control),main="Stability.Control Vs MSRP",xlab="Stability.Control",ylab="MSRP",col="gold",border="black")